Scheduling Divisible Loads on Bus Networks with Start-Up Costs by Utilizing Multiple Data Transfer Streams: PORI

2007 ◽  
Author(s):  
Jie Hu ◽  
Raymond Klefstad
Keyword(s):  
Data Transfer ◽  
Divisible Loads ◽  
Multiple Data ◽  
Start Up ◽  
Bus Networks

On the influence of start-up costs in scheduling divisible loads on bus networks

2000 ◽  
Vol 11 (12) ◽  
pp. 1288-1305 ◽  
Author(s):  
B. Veeravalli ◽  
Xiaolin Li ◽  
Chi Chung Ko
Keyword(s):  
Divisible Loads ◽  
Start Up ◽  
Bus Networks

Optimization Algorithms for Data Transfer in the Grid Environment

2012 ◽  
pp. 502-516
Author(s):  
Muzhou Xiong ◽  
Hai Jin
Keyword(s):  
Data Transfer ◽  
Optimization Algorithms ◽  
Experimental Results ◽  
Grid Environment ◽  
Transfer Data ◽  
Multiple Data ◽  
Transfer Channel ◽  
Efficient Data ◽  
Global Connection

In this chapter, two algorithms have been presented for supporting efficient data transfer in the Grid environment. From a node’s perspective, a multiple data transfer channel can be formed by selecting some other nodes as relays in data transfer. One algorithm requires the sender to be aware of the global connection information while another does not. Experimental results indicate that both algorithms can transfer data efficiently under various circumstances.

Employment of Telemedicine in Emergency Medicine

2014 ◽  
Vol 53 (02) ◽  
pp. 99-107 ◽  
Author(s):  
S. Bergrath ◽  
R. Rossaint ◽  
S. Thelen ◽  
T. Brodziak ◽  
B. Valentin ◽  
...  
Keyword(s):  
Data Transfer ◽  
Field Tests ◽  
Test System ◽  
Third Generation ◽  
Improve Quality ◽  
Network Availability ◽  
Start Up ◽  
Universal Mobile Telecommunications System ◽  
Audio Communication ◽  
System Properties

SummaryObjectives: Demographic change, rising comorbidity and an increasing number of emer -gencies are the main challenges that emer -gency medical services (EMS) in several countries worldwide are facing. In order to improve quality in EMS, highly trained personnel and well-equipped ambulances are essential. However several studies have shown a deficiency in qualified EMS physicians. Telemedicine emerges as a complementary system in EMS that may provide expertise and improve quality of medical treatment on the scene. Hence our aim is to develop and test a specific teleconsultation system.Methods: During the development process several use cases were defined and technically specified by medical experts and en -gineers in the areas of: system administration, start-up of EMS assistance systems, audio communication, data transfer, routine tele-EMS physician activities and research capabilities. Upon completion, technical field tests were performed under realistic conditions to test system properties such as robustness, feasibility and usability, providing end-to-end measurements.Results: Six ambulances were equipped with telemedical facilities based on the results of the requirement analysis and 55 scenarios were tested under realistic conditions in one month. The results indicate that the developed system performed well in terms of usability and robustness. The major challenges were, as expected, mobile communication and data network availability. Third generation networks were only available in 76.4% of the cases. Although 3G (third generation), such as Universal Mobile Telecommunications System (UMTS), provides beneficial conditions for higher bandwidth, system performance for most features was also acceptable under adequate 2G (second generation) test conditions.Conclusions: An innovative concept for the use of telemedicine for medical consultations in EMS was developed. Organisational and technical aspects were considered and practical requirements specified. Since technical feasibility was demonstrated in these technical field tests, the next step would be to prove medical usefulness and technical robustness under real conditions in a clinical trial.

scholarly journals SIMPLER MAGIC: Synthesis and Mapping of In-Memory Logic Executed in a Single Row to Improve Throughput

2020 ◽  
Author(s):  
Rotem Ben-Hur ◽  
Ronny Ronen ◽  
Ameer Haj-Ali ◽  
Debjyoti Bhattacharjee ◽  
Adi Eliahu ◽  
...  
Keyword(s):  
Computer Architecture ◽  
Data Transfer ◽  
Logic Function ◽  
Logical Function ◽  
Single Row ◽  
Area Efficiency ◽  
Modern Computer ◽  
Multiple Data ◽  
Memory Mapping ◽  
Logic Operations

In-memory processing can dramatically improve the latency and energy consumption of computing systems by minimizing the data transfer between the memory and the processor. Efficient execution of processing operations within the memory is therefore a highly motivated objective in modern computer architecture. This paper presents a novel automatic framework for efficient implementation of arbitrary combinational logic functions within a memristive memory. Using tools from logic design, graph theory and compiler register allocation technology, we developed SIMPLER (Synthesis and In-memory MaPping of Logic Execution in a single Row), a tool that optimizes the execution of in-memory logic operations in terms of throughput and area. Given a logical function, SIMPLER automatically generates a sequence of atomic Memristor-Aided loGIC (MAGIC) NOR operations and efficiently locates them within a single size-limited memory row, reusing cells to save area when needed. This approach fully exploits the parallelism offered by the MAGIC NOR gates. It allows multiple instances of the logic function to be performed concurrently, each compressed into a single row of the memory. This virtue makes SIMPLER an attractive candidate for designing in-memory Single Instruction, Multiple Data (SIMD) operations. Compared to previous work (that optimizes latency rather than throughput for a single function), SIMPLER achieves an average throughput improvement of 435×. When previous tools are parallelized similarly to SIMPLER, SIMPLER achieves higher throughput of at least 5×, with 23× improvement in area and 20× improvement in area efficiency. These improvements more than fully compensate for the increase (up to 17% on average) in latency.

scholarly journals SIMPLER MAGIC: Synthesis and Mapping of In-Memory Logic Executed in a Single Row to Improve Throughput

2020 ◽  
Author(s):  
Rotem Ben-Hur ◽  
Ronny Ronen ◽  
Ameer Haj-Ali ◽  
Debjyoti Bhattacharjee ◽  
Adi Eliahu ◽  
...  
Keyword(s):  
Computer Architecture ◽  
Data Transfer ◽  
Logic Function ◽  
Logical Function ◽  
Single Row ◽  
Area Efficiency ◽  
Modern Computer ◽  
Multiple Data ◽  
Memory Mapping ◽  
Logic Operations

In-memory processing can dramatically improve the latency and energy consumption of computing systems by minimizing the data transfer between the memory and the processor. Efficient execution of processing operations within the memory is therefore a highly motivated objective in modern computer architecture. This paper presents a novel automatic framework for efficient implementation of arbitrary combinational logic functions within a memristive memory. Using tools from logic design, graph theory and compiler register allocation technology, we developed SIMPLER (Synthesis and In-memory MaPping of Logic Execution in a single Row), a tool that optimizes the execution of in-memory logic operations in terms of throughput and area. Given a logical function, SIMPLER automatically generates a sequence of atomic Memristor-Aided loGIC (MAGIC) NOR operations and efficiently locates them within a single size-limited memory row, reusing cells to save area when needed. This approach fully exploits the parallelism offered by the MAGIC NOR gates. It allows multiple instances of the logic function to be performed concurrently, each compressed into a single row of the memory. This virtue makes SIMPLER an attractive candidate for designing in-memory Single Instruction, Multiple Data (SIMD) operations. Compared to previous work (that optimizes latency rather than throughput for a single function), SIMPLER achieves an average throughput improvement of 435×. When previous tools are parallelized similarly to SIMPLER, SIMPLER achieves higher throughput of at least 5×, with 23× improvement in area and 20× improvement in area efficiency. These improvements more than fully compensate for the increase (up to 17% on average) in latency.

scholarly journals Not in Name Alone: A Memristive Memory Processing Unit for Real In-Memory Processing

2020 ◽  
Author(s):  
Ameer Haj-Ali ◽  
Nimrod Wald ◽  
Ronny Ronen ◽  
Shahar Kvatinsky ◽  
Rotem Ben-Hur
Keyword(s):  
Data Transfer ◽  
Single Instruction Multiple Data ◽  
Processing Unit ◽  
Von Neumann ◽  
Data Movement ◽  
Memory Processing ◽  
Data Intensive ◽  
Root Cause ◽  
Multiple Data ◽  
Data Intensive Applications

<div>Data movement between processing and memory is</div><div>the root cause of the limited performance and energy</div><div>efficiency in modern von Neumann systems. To</div><div>overcome the data-movement bottleneck, we present</div><div>the memristive Memory Processing Unit (mMPU)—a</div><div>real processing-in-memory system in which the computation is done directly in the</div><div>memory cells, thus eliminating the necessity for data transfer. Furthermore, with its</div><div>enormous inner parallelism, this system is ideal for data-intensive applications that are</div><div>based on single instruction, multiple data (SIMD)—providing high throughput and</div><div>energy-efficiency.</div>

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